prepare_mapping_workflow#

Autogenerated DPF operator classes.

class ansys.dpf.core.operators.geo.prepare_mapping_workflow.prepare_mapping_workflow(input_support=None, output_support=None, filter_radius=None, influence_box=None, config=None, server=None)#

Generate a workflow that can map results from a support to another one.

Parameters
  • input_support (Field or MeshedRegion) –

  • output_support (Field or MeshedRegion) –

  • filter_radius (float) – Radius size for the rbf filter

  • influence_box (float, optional) –

Examples

>>> from ansys.dpf import core as dpf
>>> # Instantiate operator
>>> op = dpf.operators.geo.prepare_mapping_workflow()
>>> # Make input connections
>>> my_input_support = dpf.Field()
>>> op.inputs.input_support.connect(my_input_support)
>>> my_output_support = dpf.Field()
>>> op.inputs.output_support.connect(my_output_support)
>>> my_filter_radius = float()
>>> op.inputs.filter_radius.connect(my_filter_radius)
>>> my_influence_box = float()
>>> op.inputs.influence_box.connect(my_influence_box)
>>> # Instantiate operator and connect inputs in one line
>>> op = dpf.operators.geo.prepare_mapping_workflow(
...     input_support=my_input_support,
...     output_support=my_output_support,
...     filter_radius=my_filter_radius,
...     influence_box=my_influence_box,
... )
>>> # Get output data
>>> result_mapping_workflow = op.outputs.mapping_workflow()
static default_config(server=None)#

Returns the default config of the operator.

This config can then be changed to the user needs and be used to instantiate the operator. The Configuration allows to customize how the operation will be processed by the operator.

Parameters

server (server.DPFServer, optional) – Server with channel connected to the remote or local instance. When None, attempts to use the global server.

property inputs#

Enables to connect inputs to the operator

Returns

inputs

Return type

InputsPrepareMappingWorkflow

property outputs#

Enables to get outputs of the operator by evaluationg it

Returns

outputs

Return type

OutputsPrepareMappingWorkflow

property config#

Copy of the operator’s current configuration.

You can modify the copy of the configuration and then use operator.config = new_config or create an operator with the new configuration as a parameter.

Returns

Copy of the operator’s current configuration.

Return type

ansys.dpf.core.config.Config

connect(pin, inpt, pin_out=0)#

Connect an input on the operator using a pin number.

Parameters
  • pin (int) – Number of the input pin.

  • inpt (str, int, double, bool, list[int], list[float], Field, FieldsContainer, Scoping,) –

  • ScopingsContainer – Operator, os.PathLike Object to connect to.

  • MeshedRegion – Operator, os.PathLike Object to connect to.

  • MeshesContainer – Operator, os.PathLike Object to connect to.

  • DataSources – Operator, os.PathLike Object to connect to.

  • CyclicSupport – Operator, os.PathLike Object to connect to.

  • Outputs – Operator, os.PathLike Object to connect to.

  • pin_out (int, optional) – If the input is an operator, the output pin of the input operator. The default is 0.

Examples

Compute the minimum of displacement by chaining the "U" and "min_max_fc" operators.

>>> from ansys.dpf import core as dpf
>>> from ansys.dpf.core import examples
>>> data_src = dpf.DataSources(examples.multishells_rst)
>>> disp_op = dpf.operators.result.displacement()
>>> disp_op.inputs.data_sources(data_src)
>>> max_fc_op = dpf.operators.min_max.min_max_fc()
>>> max_fc_op.inputs.connect(disp_op.outputs)
>>> max_field = max_fc_op.outputs.field_max()
>>> max_field.data
DPFArray([[0.59428386, 0.00201751, 0.0006032 ]]...
eval(pin=None)#

Evaluate this operator.

Parameters

pin (int) – Number of the output pin. The default is None.

Returns

output – Returns the first output of the operator by default and the output of a given pin when specified. Or, it only evaluates the operator without output.

Return type

FieldsContainer, Field, MeshedRegion, Scoping

Examples

Use the eval method.

>>> from ansys.dpf import core as dpf
>>> import ansys.dpf.core.operators.math as math
>>> from ansys.dpf.core import examples
>>> data_src = dpf.DataSources(examples.multishells_rst)
>>> disp_op = dpf.operators.result.displacement()
>>> disp_op.inputs.data_sources(data_src)
>>> normfc = math.norm_fc(disp_op).eval()
get_output(pin=0, output_type=None)#

Retrieve the output of the operator on the pin number.

To activate the progress bar for server version higher or equal to 3.0, use my_op.progress_bar=True

Parameters
  • pin (int, optional) – Number of the output pin. The default is 0.

  • output_type (ansys.dpf.core.common.types, type, optional) – Requested type of the output. The default is None.

Returns

Output of the operator.

Return type

type

static operator_specification(op_name, server=None)#

Documents an Operator with its description (what the Operator does), its inputs and outputs and some properties

property progress_bar: bool#

With this property, the user can choose to print a progress bar when the operator’s output is requested, default is False

run()#

Evaluate this operator.

property specification#

Returns the Specification (or documentation) of this Operator

Return type

Specification

class ansys.dpf.core.operators.geo.prepare_mapping_workflow.InputsPrepareMappingWorkflow(op: ansys.dpf.core.dpf_operator.Operator)#

Intermediate class used to connect user inputs to prepare_mapping_workflow operator.

Examples

>>> from ansys.dpf import core as dpf
>>> op = dpf.operators.geo.prepare_mapping_workflow()
>>> my_input_support = dpf.Field()
>>> op.inputs.input_support.connect(my_input_support)
>>> my_output_support = dpf.Field()
>>> op.inputs.output_support.connect(my_output_support)
>>> my_filter_radius = float()
>>> op.inputs.filter_radius.connect(my_filter_radius)
>>> my_influence_box = float()
>>> op.inputs.influence_box.connect(my_influence_box)
property input_support#

Allows to connect input_support input to the operator.

Parameters

my_input_support (Field or MeshedRegion) –

Examples

>>> from ansys.dpf import core as dpf
>>> op = dpf.operators.geo.prepare_mapping_workflow()
>>> op.inputs.input_support.connect(my_input_support)
>>> # or
>>> op.inputs.input_support(my_input_support)
property output_support#

Allows to connect output_support input to the operator.

Parameters

my_output_support (Field or MeshedRegion) –

Examples

>>> from ansys.dpf import core as dpf
>>> op = dpf.operators.geo.prepare_mapping_workflow()
>>> op.inputs.output_support.connect(my_output_support)
>>> # or
>>> op.inputs.output_support(my_output_support)
property filter_radius#

Allows to connect filter_radius input to the operator.

Radius size for the rbf filter

Parameters

my_filter_radius (float) –

Examples

>>> from ansys.dpf import core as dpf
>>> op = dpf.operators.geo.prepare_mapping_workflow()
>>> op.inputs.filter_radius.connect(my_filter_radius)
>>> # or
>>> op.inputs.filter_radius(my_filter_radius)
property influence_box#

Allows to connect influence_box input to the operator.

Parameters

my_influence_box (float) –

Examples

>>> from ansys.dpf import core as dpf
>>> op = dpf.operators.geo.prepare_mapping_workflow()
>>> op.inputs.influence_box.connect(my_influence_box)
>>> # or
>>> op.inputs.influence_box(my_influence_box)
connect(inpt)#

Connect any input (an entity or an operator output) to any input pin of this operator. Searches for the input type corresponding to the output.

Parameters
  • inpt (str, int, double, bool, list[int], list[float], Field, FieldsContainer, Scoping,) –

  • ScopingsContainer (E501) – Input of the operator.

  • MeshedRegion (E501) – Input of the operator.

  • MeshesContainer (E501) – Input of the operator.

  • DataSources (E501) – Input of the operator.

  • CyclicSupport (E501) – Input of the operator.

  • Outputs (E501) – Input of the operator.

  • noqa (os.PathLike #) – Input of the operator.

class ansys.dpf.core.operators.geo.prepare_mapping_workflow.OutputsPrepareMappingWorkflow(op: ansys.dpf.core.dpf_operator.Operator)#

Intermediate class used to get outputs from prepare_mapping_workflow operator.

Examples

>>> from ansys.dpf import core as dpf
>>> op = dpf.operators.geo.prepare_mapping_workflow()
>>> # Connect inputs : op.inputs. ...
>>> result_mapping_workflow = op.outputs.mapping_workflow()
property mapping_workflow#

Allows to get mapping_workflow output of the operator

Returns

my_mapping_workflow

Return type

Workflow

Examples

>>> from ansys.dpf import core as dpf
>>> op = dpf.operators.geo.prepare_mapping_workflow()
>>> # Connect inputs : op.inputs. ...
>>> result_mapping_workflow = op.outputs.mapping_workflow()